Integrated Sensing and Processing for Hyperspectral Imagery
In this chapter, we present an information sensing system which integrates sensing and processing resulting in the direct collection of data which is relevant to the application. Broadly, integrated sensing and processing (ISP) considers algorithms that are integrated with the collection of data. That is, traditional sensor development tries to come up with the “best” sensor in terms of SNR, resolution, data rates, integration time, and so forth, while traditional algorithm development tasks might wish to optimize probability of detection, false alarm rate, and class separability. For a typical automatic target recognition (ATR) problem, the goal of ISP is to field algorithms which “tell” the sensor what kind of data to collect next and the sensor alters its parameters to collect the “best” information in order that the algorithm performs optimally. We illustrate the concept of ISP using a near Infrared (NIR) hyperspectral imaging sensor. This prototype sensor incorporates a digital mirror array (DMA) device in order to realize a Hadamard multiplexed imaging system. Specific Hadamard codes can be sent to the sensor to realize inner products of the underlying scene rather than the scene itself. The developed ISP algorithms utilize these codes to overcome issues traditionally associated with hyperspectral imaging (i.e. Data Glut and SNR issues) while also performing a object detection task. The underlying integration of the sensing and processing results in algorithms which have better overall performance while collecting less data.
KeywordsHyperspectral imaging Adaptive imaging Compressive imaging Hadamard multiplexing
- 3.Wuttig, A., Riesenberg, R.: Sensitive Hadamard transform imaging spectrometer with a simple MEMS. In: Proceedings of SPIE 4881, pp. 167–178 (2003)Google Scholar
- 4.Donoho, D.L.: Compressed sensing, Stanford University: Department of Statistics report 2004-25, October, 2004Google Scholar
- 7.Mahalanobis, A., Daniell, C.: Data compression and correlation filtering: a seamless approach to pattern recognition. In: Javidi, B. (ed.) Smart Imaging Systems. SPIE Press, Bellingham (2001)Google Scholar
- 9.Fateley, W.G., Coifman, R.R., Geshwind, F., DeVerse, R.A.: System and method for encoded spatio-spectral information processing. US Patent # 6,859,275, February 2005Google Scholar